Deep Learning for Computer Vision with Tensorflow 2.X

🚀 Course Title: Deep Learning for Computer Vision with TensorFlow 2.X: Updated Edition! 🌟

🎉 Headline: Updated Version of the Previous Hit Course! SOTAs like Vision Transformer, YOLOv7, and U-Net Included!

🚀 About This Course: Dive into the world of Computer Vision with TensorFlow 2.X, where we explore state-of-the-art (SOTA) algorithms using the latest advancements in deep learning. Designed for all levels, this course is particularly beneficial for those without a GPU, as it was entirely developed using Google Colaboratory (Colab). Whether you have a local GPU or not, follow along and master the intricacies of image classification and object detection with practical applications.

📚 What You'll Learn:

• Image Fundamentals in Computer Vision
• Load images in Generators with TensorFlow
• Convolution Operation and its variants
• Sparsity Connections, Parameter Sharing, Depthwise Separable Convolution, Padding, Conv2D layer, etc.
• U-Net for Image Segmentation with attention mechanism
• Hands-on practice with datasets like MRI images for brain tumor detection 🧠

🎓 Curriculum Highlights:

• Detailed review of the theory behind YOLO (You Only Look Once) versions including YOLOv4 and the latest YOLOv7
• Practical applications ranging from detecting robots, to face mask detection, and even license plate recognition using OCR (Optical Character Recognition) 🛑🎭🎉
• Step-by-step guidance on how to apply U-Net for complex image segmentation tasks

💡 Why Take This Course? This course is a significant upgrade from its predecessor, which was highly praised by students:

• ⭐️ Maximiliano D'Amico: "Very interesting and updated course on YOLO!"
• ⭐️ Stefan Lankester: "Thanks Carlos for this valuable training. Good explanation with broad treatment of the subject."
• ⭐️ Shihab de Sena Filho: "Excellent course. Best machine learning course for computer vision."
• ⭐️ Areej AI Medinah: "The course is really good for computer vision. It consists of all material required to put projects in practice."
• ⭐️ Dave Roberto: "The course is completely worth it. Clear explanation of concepts and unique schemes that are incredibly helpful."

🤝 Who Is This For? Whether you're a beginner eager to understand the basics, an intermediate looking to deepen your knowledge, or an advanced user aiming to stay ahead of the curve with the latest techniques, this course is tailored for you.

🔍 What's Covered:

• Deep learning and neural networks in TensorFlow 2.X
• Convolutional Neural Networks (CNNs) for image recognition and classification
• Object detection with YOLO, including the latest versions
• Image segmentation with U-Net
• Practical projects using real-world datasets

🎥 Learning Format:

• Expertly crafted video lectures
• Interactive coding exercises with step-by-step explanations
• Real-world case studies and applications
• Supplementary resources to enhance your learning experience

Join us on this journey to master Deep Learning for Computer Vision with TensorFlow 2.X! Enhance your skills, explore cutting-edge technologies, and transform your understanding of AI through practical, hands-on learning. Sign up now and be part of the future of computer vision! 🌐✨